AIMC Topic: Deep Learning

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Detection and Localization of Spine Disorders from Plain Radiography.

Journal of imaging informatics in medicine
Spine disorders can cause severe functional limitations, including back pain, decreased pulmonary function, and increased mortality risk. Plain radiography is the first-line imaging modality to diagnose suspected spine disorders. Nevertheless, radiog...

Automated Segmentation of Lymph Nodes on Neck CT Scans Using Deep Learning.

Journal of imaging informatics in medicine
Early and accurate detection of cervical lymph nodes is essential for the optimal management and staging of patients with head and neck malignancies. Pilot studies have demonstrated the potential for radiomic and artificial intelligence (AI) approach...

Predicting Therapeutic Response to Hypoglossal Nerve Stimulation Using Deep Learning.

The Laryngoscope
OBJECTIVES: To develop and validate machine learning (ML) and deep learning (DL) models using drug-induced sleep endoscopy (DISE) images to predict the therapeutic efficacy of hypoglossal nerve stimulator (HGNS) implantation.

Uncertainty-aware multiple-instance learning for reliable classification: Application to optical coherence tomography.

Medical image analysis
Deep learning classification models for medical image analysis often perform well on data from scanners that were used to acquire the training data. However, when these models are applied to data from different vendors, their performance tends to dro...

Preoperative CT-based radiomics and deep learning model for predicting risk stratification of gastric gastrointestinal stromal tumors.

Medical physics
BACKGROUND: Gastrointestinal stromal tumors (GISTs) are clinically heterogeneous with various malignant potential in different individuals. It is crucial to explore a reliable method for preoperative risk stratification of gastric GISTs noninvasively...

Deep Deblurring in Teledermatology: Deep Learning Models Restore the Accuracy of Blurry Images' Classification.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Blurry images in teledermatology and consultation increased the diagnostic difficulty for both deep learning models and physicians. We aim to determine the extent of restoration in diagnostic accuracy after blurry images are deblurred by deep learni...

High-accuracy heart rate detection using multispectral IPPG technology combined with a deep learning algorithm.

Journal of biophotonics
Image Photoplethysmography (IPPG) technology is a noncontact physiological parameter detection technology, which has been widely used in heart rate (HR) detection. However, traditional imaging devices still have issues such as narrower receiving spec...

Fragment-Fusion Transformer: Deep Learning-Based Discretization Method for Continuous Single-Cell Raman Spectral Analysis.

ACS sensors
Raman spectroscopy has become an important single-cell analysis tool for monitoring biochemical changes at the cellular level. However, Raman spectral data, typically presented as continuous data with high-dimensional characteristics, is distinct fro...

Optical imaging for diabetic retinopathy diagnosis and detection using ensemble models.

Photodiagnosis and photodynamic therapy
Diabetes, characterized by heightened blood sugar levels, can lead to a condition called Diabetic Retinopathy (DR), which adversely impacts the eyes due to elevated blood sugar affecting the retinal blood vessels. The most common cause of blindness i...